Tool wear has been extensively studied by the machine tool industry and academia for over 50 years. In general, research has focused on correlating tool wear with machining signals, mainly cutting forces, tool vibration, and cutting temperature, to provide the necessary process information needed for the development of intelligent unmanned machining systems. Although these machining signals can be easily measured, an accurate and reliable method of measuring cutting tool wear has not been developed and thus the accurate correlation of machining signals to tool wear has not been possible.
During machining, the failure of a cutting tool is caused by wear due to the interactions between the tool and the workpiece (flank wear and between the tool and the chip (crater wear). Guidelines and specifications for flank and crater wear measurement are available in machining handbooks. Traditionally, these small wear parameters are measured under laboratory conditions, using a toolmaker's microscope. However, these measurements provide a limited definition of the wear of a cutting edge. Tool wear is not simple in nature and because of the irregular boundaries and the varying surface textures, the flank and crater wear boundaries are difficult to define. As a result, measurements of the width or length of flank and crater wear contours are only approximations and are not repeatable because of measurement error. Moreover, it has been recognized by those skilled in the art that the area of a wear region is a more relevant parameter for quantifying tool wear, but there has been no practical, accurate method for measuring the irregular wear areas. For these reasons, a computer vision technique to measure tool wear was developed.